standard app name
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214
habits.py
214
habits.py
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import pandas as pd
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import vobject
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import requests
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from datetime import datetime, date
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import matplotlib.pyplot as plt
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import calmap
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import streamlit as st
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import plotly.express as px
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import plotly.graph_objects as go
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import json
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import os
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# Function to load data from a JSON file
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def load_data(file_path):
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try:
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with open(file_path, 'r') as file:
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if os.path.getsize(file_path) == 0: return {}
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return json.load(file)
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except FileNotFoundError:
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print("settings file not found")
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return {}
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except :
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print("settings file invalid")
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return {}
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# Function to save data to a JSON file
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def save_data(file_path, data):
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with open(file_path, 'w') as file:
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json.dump(data, file)
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# Function to create a calendar heatmap for a specific year
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def create_calendar_heatmap(event_series, year):
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# Filter the series to include only the specific year
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event_series_year = event_series[event_series.index.year == year]
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# Create a complete date range for the year
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all_dates_year = pd.date_range(start=f'{year}-01-01', end=f'{year}-12-31')
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# Reindex the Series to include all dates in the year and fill missing dates with zero
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event_series_year = event_series_year.reindex(all_dates_year, fill_value=0)
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# Create a DataFrame for Plotly
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df_year = pd.DataFrame({'Date': event_series_year.index, 'Events': event_series_year.values})
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# Generate day of the week and week of the year
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df_year['DayOfWeek'] = df_year['Date'].dt.dayofweek
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df_year['WeekOfYear'] = df_year['Date'].dt.isocalendar().week
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df_year['Month'] = df_year['Date'].dt.strftime('%b')
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# Create the Plotly figure
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fig = go.Figure(data=go.Heatmap(
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z=df_year['Events'],
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x=df_year['WeekOfYear'],
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y=df_year['DayOfWeek'],
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colorscale='YlGn',
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showscale=True,
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colorbar=dict(
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title='# of Events',
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orientation='h', # Set the color scale to horizontal
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len=0.3, # Adjust the length of the color scale
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thickness=10,
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x=0.98,
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y=1,
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xanchor="right",
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yanchor="bottom", # Position the color scale at the bottom
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),
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hoverinfo='z+x+y'
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))
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# Set the aspect ratio to ensure square boxes
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fig.update_yaxes(scaleanchor="x", scaleratio=1, constrain="domain")
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# Update the layout with the axes
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fig.update_layout(
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title=f'Calendar Heatmap for {year}',
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yaxis=dict(
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tickmode='array',
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tickvals=[0, 1, 2, 3, 4, 5, 6],
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ticktext=['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday'],
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range=[-1.2, 6.5], # Adjust the range to eliminate space
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automargin=True, # Adjust margins automatically
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domain=[0.1,0.95] # Use available space effectively
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),
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xaxis=dict(
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tickmode='array',
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tickvals=list(range(1, 54)),
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ticktext=list(range(1, 54)),
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title=dict(
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text='Weeks of the Year',
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standoff=0
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),
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title_standoff=0, # Adjust the distance of the title from the axis
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tickangle=-90, # Adjust the angle of the week numbers
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ticklen=2,
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side='top', # Display x-axis ticks above the heatmap
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automargin=True, # Adjust margins automatically
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),
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autosize=True,
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margin=dict(
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l=50,
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r=50,
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b=30, # Increase bottom margin to fit month names
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t=30, # Increase top margin to fit week numbers
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pad=0
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),
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height=450, # Fixed height to avoid excessive space
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)
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# Add month annotations with arrows at the bottom
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month_starts = df_year.iloc[:-10].groupby('Month')['WeekOfYear'].min().to_dict()
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for month, week in month_starts.items():
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fig.add_annotation(
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x=week,
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y=-0.5, # Position below the x-axis
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text=month,
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showarrow=False,
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arrowhead=2,
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ax=week,
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ay=0, # Position the arrow closer
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xref="x",
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yref="y",
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#font=dict(size=12, color="black"),
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xanchor='left',
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yanchor='top'
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)
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return fig
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def save_load():
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st.session_state['options'].pop("New")
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save_data(settings_file, st.session_state['options'])
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st.session_state['options'] = load_data(settings_file)
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def update_params():
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st.session_state['cal_url'] = st.session_state['options'][st.session_state['setup']]['cal_url']
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st.session_state['number_of_years'] = st.session_state['options'][st.session_state['setup']]['number_of_years']
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# set webpage title
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st.title("Yearly Activity Heatmaps")
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# File path for data storage
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settings_file = 'settings.json'
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# Load persisted data if it exists; set default values otherwise
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st.session_state['options'] = load_data(settings_file)
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st.session_state['options']["New"] = {
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'cal_url':"https://canada-holidays.ca/ics?cd=true",
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'number_of_years': 3
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}
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# Get the Calendar Export link and number of years from sidebar menu
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st.sidebar.header("Settings")
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st.session_state['setup'] = st.sidebar.selectbox("Choose a Setup:", st.session_state['options'].keys())
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st.session_state['cal_url'] = st.sidebar.text_input("Enter The Calendar Export Link:", value=st.session_state['options'][st.session_state['setup']]['cal_url'])
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st.session_state['number_of_years'] = st.sidebar.number_input("Enter the number of years:", min_value=1, max_value=10, value=st.session_state['options'][st.session_state['setup']]['number_of_years'])
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update_params()
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if(st.session_state['setup'] == "New"):
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setup_save_name = st.sidebar.text_input("Setup Save Name:", value='yahoo')
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st.session_state['options'][setup_save_name] = {
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'cal_url': st.session_state['cal_url'],
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'number_of_years': st.session_state['number_of_years']
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}
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st.sidebar.button("Save",on_click=save_load)
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response = requests.get(st.session_state['cal_url'])
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if response.status_code == 200:
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# Parse the .ics file
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cal = vobject.readOne(response.text)
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else:
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print("Failed to download the file")
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# Create a dictionary to store event counts by date
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event_counts = {}
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for component in cal.components():
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if component.name == "VEVENT":
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event_date = component.dtstart.value
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if isinstance(event_date, datetime):
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event_date = event_date.date()
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if event_date in event_counts:
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event_counts[event_date] += 1
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else:
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event_counts[event_date] = 1
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# Convert the dictionary to a pandas Series
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event_series = pd.Series(event_counts)
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# Ensure the index is in datetime format
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event_series.index = pd.to_datetime(event_series.index)
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# Get the current year
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current_year = datetime.now().year
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# Create a list of years to plot
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years_to_plot = [current_year - i for i in range(st.session_state['number_of_years'])]
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# Plot each year's data
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for year in years_to_plot:
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fig = create_calendar_heatmap(event_series, year)
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st.plotly_chart(fig)
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